Computational current sensor

ABSTRACT

A computational current sensor, that enhances traditional Kalman filter based current observer techniques, with transient tracking enhancements and an online parasitic parameter identification that enhances overall accuracy during steady state and transient events while guaranteeing convergence. During transient operation (e.g., a voltage droop), a main filter is bypassed with estimated values calculated from a charge balance principle to enhance accuracy while tracking transient current surges of the DC-DC converter. To address the issue of dependency on a precise model parameter information and further improve accuracy, an online identification algorithm is included to track the equivalent parasitic resistance at run-time.

BACKGROUND

Inductor current (I_(L)) is a key variable in DC-DC converters. I_(L) sensing is a core component in current mode control where the feedback loop relies on a sampled inductor current for closed-loop control. I_(L) can also serve as a metric for operating mode transition (e.g., continuous conduction mode (CCM) to discontinuous conduction mode (DCM)) and overload protection in buck converters. In such application scenarios, high speed and accurate current sensors are vital to achieve desired performance. With conventional analog current sensing techniques, it is challenging to maintain wide bandwidth and high accuracy across a wide dynamic range.

For example, in analog current sensing techniques, device and layout mismatch, and package parasitic induced voltage noise are critical issues impacting sensing accuracy. Larger area and higher power consumption are traded off for accurate current sensing. Low bandwidth is another limitation of existing analog I_(L) sensing technique. In such techniques, there is a bunch of trim needed to maintain accuracy across a wide dynamic range of currents and adds a lot of fuses to the overall design increasing cost.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments of the disclosure will be understood more fully from the detailed description given below and from the accompanying drawings of various embodiments of the disclosure, which, however, should not be taken to limit the disclosure to the specific embodiments, but are for explanation and understanding only.

FIG. 1 illustrates an architecture of computational current sensor, in accordance with some embodiments.

FIG. 2 illustrates a set of plots showing online R_(eq) identification operation during initial ramp-up, in accordance with some embodiments.

FIG. 3 illustrates a set of plots showing simulated ideal and fixed-point computational algorithm response during load transient, in accordance with some embodiments.

FIG. 4 illustrates a set of plots showing simulated ideal and fixed-point computational algorithm response under lineside disturbances, in accordance with some embodiments.

FIG. 5 illustrates a set of plots showing simulated ideal and fixed-point computational algorithm response for Vref tracking operation, in accordance with some embodiments.

FIG. 6 illustrates a set of plots showing simulated online parameter tracking of temperature induced Req variation, in accordance with some embodiments.

FIG. 7 illustrates an architecture where computational current sensor is used for monitoring health of a voltage regulator, in accordance with some embodiments.

FIG. 8 illustrates an architecture where computational current sensor is used for efficiency tracking of the voltage regulator, in accordance with some embodiments.

FIG. 9 illustrates a system-on-chip (SoC) with computational current sensor, in accordance with some embodiments.

DETAILED DESCRIPTION

Some embodiments describe a computational current sensor, that enhances a traditional Kalman filter based current observer techniques, with transient tracking enhancements and an online parasitic parameter identification that enhances overall accuracy during steady state and transient events while guaranteeing convergence. During transient operation (e.g., a voltage droop, sudden workload demand) experienced at an output voltage rail of a DC-DC converter, a main filter is bypassed with estimated values calculated from a charge balance principle to enhance accuracy while tracking transient current surges of the DC-DC converter. To address the issue of dependency on a precise model parameter information and further improve accuracy, various embodiments include an online identification algorithm to track an equivalent parasitic resistance at run-time. The equivalent parasitic resistance models the resistance through the output supply rail. Various embodiments are described with reference to a DC-DC converter such as a buck, boost, buck-boost converters, etc. However, the embodiments are also applicable to linear converters such as low dropout (LDO) regulators (with or without an inductor) in analog, digital, or mixed signal configurations.

In some embodiments, an apparatus is provided which comprises a voltage regulator to provide power to an output supply rail; and a current sensor coupled to the voltage regulator. In some embodiments, the current sensor includes a Kalman filter with a first logic to estimate equivalent resistance through the output supply rail, and with a second logic to track a transient behavior on the output supply rail. In some embodiments, a portion of the Kalman filter is bypassed based on the second logic tracking the transient behavior. In some embodiments, the Kalman filter includes a state prediction logic coupled to the first logic. In some embodiments, the current sensor comprises a multiplexer to selectively provide an estimated model for a difference in inductor current samples to the state prediction logic based on the second logic tracking the transient behavior. In some embodiments, the current sensor comprises an analog-to-digital converter (ADC) coupled to the voltage regulator, wherein the ADC is to provide digital representations of one or more parameters of the voltage regulator to the first logic and the second logic. In some embodiments, the current sensor is a digital current sensor. In some embodiments, the one or more parameters include: voltage on a switching node coupled to a high-side switch and a low-side switch; input supply voltage to the voltage regulator; and/or output supply voltage of the voltage regulator. In some embodiments, the apparatus comprises a health monitor to monitor health of the voltage regulator based on the estimated equivalent resistance from the current sensor, wherein the health monitor is to shut down the voltage regulator if aging or thermal properties are above a safe threshold. In some embodiments, the apparatus comprises an efficiency monitor to monitor efficiency of the voltage regulator based on the estimated equivalent resistance from the current sensor. In some embodiments, the voltage regulator comprises a DC-DC converter.

In some embodiments, an apparatus is provided which comprises a DC-DC converter to provide power to an output supply rail; and a current sensor coupled to the DC-DC converter. In some embodiments, the current sensor comprising a first Kalman filter and a second Kalman filter parallel to the first Kalman filter, wherein the second Kalman filter is to generate an estimated equivalent resistance through the output supply rail and to provide that estimated equivalent resistance to the first Kalman filter. In some embodiments, the current sensor includes circuitry to track a transient behavior on the output supply rail. In some embodiments, a portion of the first Kalman filter is bypassed based on the circuitry tracking the transient behavior. In some embodiments, the current sensor comprises a multiplexer to selectively provide an estimated model for a difference in inductor current samples to a state prediction logic based on the circuitry tracking the transient behavior. In some embodiments, the current sensor comprises an analog-to-digital converter (ADC) coupled to the DC-DC converter, wherein the ADC is to provide digital representations of one or more parameters of the DC-DC converter to the first Kalman filter, the second Kalman filter, and the circuitry. In some embodiments, the one or more parameters include: voltage on a switching node coupled to a high-side switch and a low-side switch; input supply voltage to the voltage regulator; and/or or output supply voltage of the voltage regulator.

There are many technical effects of the various embodiments. For example, the computational current sensing techniques guarantees convergence while maintaining high accuracy across a wide dynamic range of currents. The technique eliminates the need for an analog current sensor that suffers from poor accuracy and larger area and power requirements while being sensitive to noise on the supply of these analog amplifiers. The computational current sensor of various embodiments has better noise immunity, lower area and power overhead and requires no trim and fuses while achieving high accuracy compared to analog sensing techniques. The computational current sensor of various embodiments can also enhance the overall bandwidth of current sensing to more than, for example, 10x to 20x of traditional analog current sensors. The computational current sensor of various embodiments provides accurate output inductor current which is continuous and the same as the load current which is a direct indication of a power domain's consumption during different workloads as opposed to input current in traditional approaches which needs averaging lowering overall bandwidth. This higher bandwidth can facilitate faster mode transitions from CCM to DCM and can also be an effective throttling mechanism for a processor core during virus workloads. The computational current sensor of various embodiments also benefits from digital computation due to their ease of integration, portability across designs and capability for lower voltage operation. Since the scheme also outputs an effective series resistance of the DC-DC converter (also referred to as an integrated voltage regulator (IVR)) accurately across process, voltage, and temperature (PVT), the efficiency and the overall health of the IVR can be monitored and flagged paving the way for reduced field failures due to IVRs improving DPM. Other technical effects will be evident from the various figures and embodiments.

In the following description, numerous details are discussed to provide a more thorough explanation of embodiments of the present disclosure. It will be apparent, however, to one skilled in the art, that embodiments of the present disclosure may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring embodiments of the present disclosure.

Note that in the corresponding drawings of the embodiments, signals are represented with lines. Some lines may be thicker, to indicate more constituent signal paths, and/or have arrows at one or more ends, to indicate primary information flow direction. Such indications are not intended to be limiting. Rather, the lines are used in connection with one or more exemplary embodiments to facilitate easier understanding of a circuit or a logical unit. Any represented signal, as dictated by design needs or preferences, may actually comprise one or more signals that may travel in either direction and may be implemented with any suitable type of signal scheme.

FIG. 1 illustrates architecture 100 of computational current sensor, in accordance with some embodiments. Architecture 100 comprises a voltage regulator (e.g., a buck converter system) which includes high-side switch MPs, low-side switch MNs, inductor L, load capacitor C_(L), input supply rail Vin (e.g., that provides power by battery 101), controller 102, and pulse width modulator (PWM) 103. While the embodiments are illustrated for a buck converter, any DC-DC converter or low dropout regulator may be used for the voltage regulator. Here, input power is supplied to input power supply rail Vin via battery 101. However, any suitable source can be used to supply input power to the input power supply rail Vin. A bridge driver (not shown here) receives a pulse train from PWM 103 and drives the high-side switch MPs and low-side switch MNs. The duty cycle d[k] of the pulse train is modulated by PWM 103 according to an error term. The error term indicates a voltage difference between the output voltage Vo and a reference voltage Vref. In some embodiments, controller 102 compares Vo with Vref and instructs PWM 103 to increase or decrease the duty cycle of the pulse train. Inductor L has at least two terminals. One of the terminals is coupled to a switching node V_(SW), which his coupled to a common node between the high-side switch MPs and low-side switch MNs. The other terminal of the inductor L is coupled to the output supply rail Vo. Here, node names and signal names are interchangeably used. For example, Vo may refer to output supply rail Vo or voltage Vo depending on the context of the sentence. While a single high-side switch MPs and a low-side switch MNs is shown, there may be additional transistors in series or parallel to these switches. In some embodiments, both the high-side switch and the low-side switch have a same conductivity type. For example, both the high-side switch and the low-side switch are of n-type or p-type devices.

Architecture further comprises computational current sensor 104 coupled to the voltage regulator. In some embodiments, computational current sensor 104 comprises analog-to-digital converter (ADC) or time-to-digital converter (TDC) 104 a and an enhanced Kalman filter. ADC 104 a is an apparatus that converts continuous physical quantities (e.g., 6 voltages) to digital numbers that represent the amplitude of the physical quantities. In some embodiments, ADC 104 a converts the analog outputs V_(SW), Vin, and/or Vo to their corresponding digital representations. Any suitable ADC may be used to implement ADC 104 a. For example, ADC 104 a is one of: direct-conversion ADC (for flash ADC), two-step flash ADC, successive-approximation ADC (SAR ADC), ramp-compare ADC, Wilkinson ADC, integrating ADC, delta-encoded ADC or counter-ramp, pipeline ADC (also called subranging quantizer), sigma-delta ADC (also known as a delta-sigma ADC), time-interleaved ADC, ADC with intermediate FM stage, or time-stretch ADC. For purposes of explaining the various embodiments, ADC 105 is considered to be flash ADC. In some embodiments, ADC 105 can be replaced by a TDC. A TDC measures a time interval and converts it into a digital (binary) output.

In some embodiments, the enhanced Kalman filter comprises state estimation logic or circuitry 105, transient tracking enhancement logic or circuitry 106, multiplexer 107, state prediction logic or circuitry 108, flip-flops (FFs) 109, and equivalent resistance (Req) identification logic or circuitry 110 coupled as shown. Since, the various blocks of computational current sensor are digital circuits, the logic of these circuits can be implemented in hardware and/or software. The software may be firmware, drivers, or even an operating system. The hardware being digital in nature can be synthesized using hardware description language (e.g., RTL, Verilog, VHDL) and ported to different process technology nodes.

In the Kalman filter, the system state variables x_(k) include average inductor current i_(L,k), capacitor voltage v_(c,k) and load current i_(load,k) and the buck converter system is modeled as x_(k+1)=Ax_(k)+Bu_(k), where:

$A = \begin{pmatrix} {1 - {\frac{T_{s}}{L}\left( {R_{eq} + r_{c}} \right)}} & {- \frac{T_{s}}{L}} & {\frac{T_{s}}{L} \cdot r_{c}} \\ \frac{T_{s}}{C} & 1 & {- \frac{T_{s}}{C}} \\ 0 & 0 & 1 \end{pmatrix}$ $B = \begin{pmatrix} \begin{matrix} {\frac{T_{s}}{L} \cdot d_{k}} & 0 \end{matrix} & 0 \end{pmatrix}$ u_(k) = V_(in, k)

R_(eq) in the system model represents total equivalent resistance (energy loss) in the buck converter, including bridge on-resistance, inductor equivalent series resistance (ESR) and other converter losses. The measurement variable—converter output voltage is denoted as z_(k) and is related to the state variables by z_(k)=Hx_(k) where H=(r_(c) 0 −r_(c)). In various embodiments, the main loop operates as normal Kalman filter when no significant V_(out) transient occurs.

In some embodiments, the transient enhancement module 106 is activated during a transient event (e.g., voltage droop, or a large current draw by a load coupled to output supply rail Vo) when V_(out) (also referred to as Vo) deviates from a reference voltage significantly (e.g., more than 20%). Upon detection of a transient event, “tran_detected” is asserted, which controls multiplexer 107. State estimation logic 105 in the main loop is then bypassed (e.g., by asserted “tran_detected”) via multiplexer 107 with a fast and rough estimation as i_(L,k)−i_(L,k−1)=f(d_(k),d_(k−1),V_(in),V_(o)) and

$i_{{load},k} = {i_{L,k} - {\frac{C}{T_{s}} \cdot {\left( {v_{o,k} - v_{o,{k - 1}}} \right).}}}$

This estimation is provided by the transient tracking enhancement block of circuitry 106. The direct computed state estimation is also fed for prediction of next cycle, accelerating main filter transient convergence speed.

In some embodiments, online parasitic identification (e.g., R_(eq) identification logic 110) focuses on a parameter impacting I_(L) estimation accuracy and tracks its variations at run-time. In the buck converter application, one parameter to track is the total equivalent resistance R_(eq) and is computed based on Equation (1).

$\begin{matrix} {R_{eq} = \frac{2 \cdot \left( {{D*V_{I}} - V_{o}} \right) \cdot \left( {V_{{sw},{mid}} - V_{{sw},\min}} \right) \cdot {Lf}_{sw}}{\left( {V_{I} - V_{{sw},{mid}}} \right) \cdot \left( {V_{{sw},{mid}} - V_{o} - {r_{L,{init}}i_{L,{avg}}}} \right) \cdot D}} & (1) \end{matrix}$

where, V_(sw,mid) and V_(sw,min) represents sampled voltage of switching node (V_(sw)) at d*T_(s)/2 and d*T_(s) from the beginning of a switching clock cycle, respectively. The operation of online R_(eq) identification is demonstrated in Error! Reference source not found. FIG. 2 illustrates a set of plots 200, 220, 230, and 240, respectively, showing online R_(eq) identification operation during initial ramp-up, in accordance with some embodiments.

Referring back to FIG. 1, in some embodiments, data path optimization is performed on the original algorithm for an actual hardware implementation. In some embodiments, the Kalman gain K_(ss) is pre-calculated offline through numerical simulations and stored in a register for computation. The computation performed on-chip at every switching clock cycle includes state prediction and estimation correction (described in Equation (2)).

{circumflex over (x)} _(k) ⁻ =A{circumflex over (x)} _(k−1) +Bu _(k) & {circumflex over (x)} _(k) ={circumflex over (x)} _(k) ⁻ +K _(ss)(z _(k) −H{circumflex over (x)} _(k) ⁻)   (2)

To avoid divide operation for R_(eq) identification on Equation (1), a filter-like structure (Equation (3)) is employed to convert division to multiplication, motivated by the fact that the value of R_(eq) does not move significantly from cycle to cycle so the precise value of R_(eq) is not necessary to be computed within a cycle.

R _(eq,k) =R _(eq,k−1) +K·(N _(k) −R _(eq,k−1) ·DE _(k))   (3)

Where:

N _(k)=2(D*V _(I) −V _(o))(V _(sw,mid) −V _(sw,min))·Lf _(sw)

DE _(k)=(V _(I) −V _(sw,mid))(V _(sw,mid) −V _(o) −r _(L,init) i _(L,avg))·D

FIG. 3 illustrates a set of plots 300, 320, and 330, respectively, showing simulated ideal and fixed-point computational algorithm response during load transient, in accordance with some embodiments.

FIG. 4 illustrates a set of plots 400, 420, and 430, respectively, showing simulated ideal and fixed-point computational algorithm response under lineside disturbances, in accordance with some embodiments.

FIG. 5 illustrates a set of plots 500 and 520, respectively, showing simulated ideal and fixed-point computational algorithm response for Vref tracking operation, in accordance with some embodiments.

FIG. 6 illustrates a set of plots 600, 620, and 630, respectively, showing simulated online parameter tracking of temperature induced R_(eq) variation, in accordance with some embodiments. In this example, events with 60% variation in resistance over temperature, computational current sensor still tracks current.

System-level simulations are conducted in, for example, Simulink, to verify the viability of computational current sensor 104 under typical voltage regulator operating conditions, including load current steps FIG. 3 to FIG. 6), lineside disturbances, reference tracking and R_(eq) variation caused by temperature profile during cold-start. Simulation results show the scheme of various embodiments is fully functional and demonstrates high accuracy and bandwidth in all conditions.

FIG. 7 illustrates architecture 700 where computational current sensor is used for monitoring health of a voltage regulator, in accordance with some embodiments. Architecture 700 is same as architecture 100 but for showing bridge driver 701 (discussed with reference to FIG. 1), compensator 702 (e.g., part of controller 102), and feedback mechanism shown as IVR (integrated voltage regulator) health monitor 703. The identified effective series resistance R_(eq) from computational current sensor 104 of the converter contains useful information for IVR health monitoring. When the tracked R_(eq value) is too high compared to the nominal resistance for the operating condition, IVR health monitor 703 will flag a degraded signal and possibly shut the IVR down (via thermal/aging shutdown signal) due to temperature overheating or transistor aging.

FIG. 8 illustrates architecture 800 where computational current sensor is used for efficiency tracking of the voltage regulator, in accordance with some embodiments. Architecture 800 is same as architecture 700 but for a different use case. Here, IVR heath monitor is replaced with voltage regulator efficiency tracking logic or circuitry 803. The identified effective resistance R_(eq) also indicates converter efficiency so IVR efficiency (q) could be estimated from R_(eq) and other operating condition parameters (V_(in), V_(out), I_(L), I_(load), etc.). Based on the estimated efficiency η_(est), the number of slices (e.g., bridges which comprise high-side and low-side switches) to be turned on in the power stage can be configured dynamically to improve efficiency. These use cases of FIG. 7 and FIG. 8 can be combined in one architecture. Other use cases that can use sensed current to take an action are also contemplated within the scope of various embodiments.

FIG. 9 illustrates a system-on-chip (SoC) with computational current sensor, in accordance with some embodiments. It is pointed out that those elements of FIG. 9 having the same reference numbers (or names) as the elements of any other figure may operate or function in any manner similar to that described, but are not limited to such. In some embodiments, any of the blocks (e.g., processor cores) the computational current sensor.

In some embodiments, device 5500 represents an appropriate computing device, such as a computing tablet, a mobile phone or smart-phone, a laptop, a desktop, an Internet-of-Things (IOT) device, a server, a wearable device, a set-top box, a wireless-enabled e-reader, or the like. It will be understood that certain components are shown generally, and not all components of such a device are shown in device 5500.

In an example, the device 5500 comprises an SoC (System-on-Chip) 5501. An example boundary of the SoC 5501 is illustrated using dotted lines in FIG. 9, with some example components being illustrated to be included within SoC 5501—however, SoC 5501 may include any appropriate components of device 5500.

In some embodiments, device 5500 includes processor 5504. Processor 5504 can include one or more physical devices, such as microprocessors, application processors, microcontrollers, programmable logic devices, processing cores, or other processing implementations such as disaggregated combinations of multiple compute, graphics, accelerator, I/O and/or other processing chips. The processing operations performed by processor 5504 include the execution of an operating platform or operating system on which applications and/or device functions are executed. The processing operations include operations related to I/O (input/output) with a human user or with other devices, operations related to power management, operations related to connecting computing device 5500 to another device, and/or the like. The processing operations may also include operations related to audio I/O and/or display I/O.

In some embodiments, processor 5504 includes multiple processing cores (also referred to as cores) 5508 a, 5508 b, 5508 c. Although merely three cores 5508 a, 5508 b, 5508 c are illustrated in FIG. 9, processor 5504 may include any other appropriate number of processing cores, e.g., tens, or even hundreds of processing cores. Processor cores 5508 a, 5508 b, 5508 c may be implemented on a single integrated circuit (IC) chip. Moreover, the chip may include one or more shared and/or private caches, buses or interconnections, graphics and/or memory controllers, or other components.

In some embodiments, processor 5504 includes cache 5506. In an example, sections of cache 5506 may be dedicated to individual cores 5508 (e.g., a first section of cache 5506 dedicated to core 5508 a, a second section of cache 5506 dedicated to core 5508 b, and so on). In an example, one or more sections of cache 5506 may be shared among two or more of cores 5508. Cache 5506 may be split in different levels, e.g., level 1 (L1) cache, level 2 (L2) cache, level 3 (L3) cache, etc.

In some embodiments, processor core 5504 may include a fetch unit to fetch instructions (including instructions with conditional branches) for execution by the core 5504. The instructions may be fetched from any storage devices such as the memory 5530. Processor core 5504 may also include a decode unit to decode the fetched instruction. For example, the decode unit may decode the fetched instruction into a plurality of micro-operations. Processor core 5504 may include a schedule unit to perform various operations associated with storing decoded instructions. For example, the schedule unit may hold data from the decode unit until the instructions are ready for dispatch, e.g., until all source values of a decoded instruction become available. In one embodiment, the schedule unit may schedule and/or issue (or dispatch) decoded instructions to an execution unit for execution.

The execution unit may execute the dispatched instructions after they are decoded (e.g., by the decode unit) and dispatched (e.g., by the schedule unit). In an embodiment, the execution unit may include more than one execution unit (such as an imaging computational unit, a graphics computational unit, a general-purpose computational unit, etc.). The execution unit may also perform various arithmetic operations such as addition, subtraction, multiplication, and/or division, and may include one or more arithmetic logic units (ALUs). In an embodiment, a co-processor (not shown) may perform various arithmetic operations in conjunction with the execution unit.

Further, execution unit may execute instructions out-of-order. Hence, processor core 5504 may be an out-of-order processor core in one embodiment. Processor core 5504 may also include a retirement unit. The retirement unit may retire executed instructions after they are committed. In an embodiment, retirement of the executed instructions may result in processor state being committed from the execution of the instructions, physical registers used by the instructions being de-allocated, etc. Processor core 5504 may also include a bus unit to enable communication between components of processor core 5504 and other components via one or more buses. Processor core 5504 may also include one or more registers to store data accessed by various components of the core 5504 (such as values related to assigned app priorities and/or sub-system states (modes) association.

In some embodiments, device 5500 comprises connectivity circuitries 5531. For example, connectivity circuitries 5531 includes hardware devices (e.g., wireless and/or wired connectors and communication hardware) and/or software components (e.g., drivers, protocol stacks), e.g., to enable device 5500 to communicate with external devices. Device 5500 may be separate from the external devices, such as other computing devices, wireless access points or base stations, etc.

In an example, connectivity circuitries 5531 may include multiple different types of connectivity. To generalize, the connectivity circuitries 5531 may include cellular connectivity circuitries, wireless connectivity circuitries, etc. Cellular connectivity circuitries of connectivity circuitries 5531 refers generally to cellular network connectivity provided by wireless carriers, such as provided via GSM (global system for mobile communications) or variations or derivatives, CDMA (code division multiple access) or variations or derivatives, TDM (time division multiplexing) or variations or derivatives, 3rd Generation Partnership Project (3GPP) Universal Mobile Telecommunications Systems (UMTS) system or variations or derivatives, 3GPP Long-Term Evolution (LTE) system or variations or derivatives, 3GPP LTE-Advanced (LTE-A) system or variations or derivatives, Fifth Generation (5G) wireless system or variations or derivatives, 5G mobile networks system or variations or derivatives, 5G New Radio (NR) system or variations or derivatives, or other cellular service standards. Wireless connectivity circuitries (or wireless interface) of the connectivity circuitries 5531 refers to wireless connectivity that is not cellular, and can include personal area networks (such as Bluetooth, Near Field, etc.), local area networks (such as Wi-Fi), and/or wide area networks (such as WiMax), and/or other wireless communication. In an example, connectivity circuitries 5531 may include a network interface, such as a wired or wireless interface, e.g., so that a system embodiment may be incorporated into a wireless device, for example, a cell phone or personal digital assistant.

In some embodiments, device 5500 comprises control hub 5532, which represents hardware devices and/or software components related to interaction with one or more I/O devices. For example, processor 5504 may communicate with one or more of display 5522, one or more peripheral devices 5524, storage devices 5528, one or more other external devices 5529, etc., via control hub 5532. Control hub 5532 may be a chipset, a Platform Control Hub (PCH), and/or the like.

For example, control hub 5532 illustrates one or more connection points for additional devices that connect to device 5500, e.g., through which a user might interact with the system. For example, devices (e.g., devices 5529) that can be attached to device 5500 include microphone devices, speaker or stereo systems, audio devices, video systems or other display devices, keyboard or keypad devices, or other I/O devices for use with specific applications such as card readers or other devices.

As mentioned above, control hub 5532 can interact with audio devices, display 5522, etc. For example, input through a microphone or other audio device can provide input or commands for one or more applications or functions of device 5500. Additionally, audio output can be provided instead of, or in addition to display output. In another example, if display 5522 includes a touch screen, display 5522 also acts as an input device, which can be at least partially managed by control hub 5532. There can also be additional buttons or switches on computing device 5500 to provide I/O functions managed by control hub 5532. In one embodiment, control hub 5532 manages devices such as accelerometers, cameras, light sensors or other environmental sensors, or other hardware that can be included in device 5500. The input can be part of direct user interaction, as well as providing environmental input to the system to influence its operations (such as filtering for noise, adjusting displays for brightness detection, applying a flash for a camera, or other features).

In some embodiments, control hub 5532 may couple to various devices using any appropriate communication protocol, e.g., PCIe (Peripheral Component Interconnect Express), USB (Universal Serial Bus), Thunderbolt, High Definition Multimedia Interface (HDMI), Firewire, etc.

In some embodiments, display 5522 represents hardware (e.g., display devices) and software (e.g., drivers) components that provide a visual and/or tactile display for a user to interact with device 5500. Display 5522 may include a display interface, a display screen, and/or hardware device used to provide a display to a user. In some embodiments, display 5522 includes a touch screen (or touch pad) device that provides both output and input to a user. In an example, display 5522 may communicate directly with the processor 5504. Display 5522 can be one or more of an internal display device, as in a mobile electronic device or a laptop device or an external display device attached via a display interface (e.g., DisplayPort, etc.). In one embodiment display 5522 can be a head mounted display (HMD) such as a stereoscopic display device for use in virtual reality (VR) applications or augmented reality (AR) applications.

In some embodiments, and although not illustrated in the figure, in addition to (or instead of) processor 5504, device 5500 may include Graphics Processing Unit (GPU) comprising one or more graphics processing cores, which may control one or more aspects of displaying contents on display 5522.

Control hub 5532 (or platform controller hub) may include hardware interfaces and connectors, as well as software components (e.g., drivers, protocol stacks) to make peripheral connections, e.g., to peripheral devices 5524.

It will be understood that device 5500 could both be a peripheral device to other computing devices, as well as have peripheral devices connected to it. Device 5500 may have a “docking” connector to connect to other computing devices for purposes such as managing (e.g., downloading and/or uploading, changing, synchronizing) content on device 5500. Additionally, a docking connector can allow device 5500 to connect to certain peripherals that allow computing device 5500 to control content output, for example, to audiovisual or other systems.

In addition to a proprietary docking connector or other proprietary connection hardware, device 5500 can make peripheral connections via common or standards-based connectors. Common types can include a Universal Serial Bus (USB) connector (which can include any of a number of different hardware interfaces), DisplayPort including MiniDisplayPort (MDP), High Definition Multimedia Interface (HDMI), Firewire, or other types.

In some embodiments, connectivity circuitries 5531 may be coupled to control hub 5532, e.g., in addition to, or instead of, being coupled directly to the processor 5504. In some embodiments, display 5522 may be coupled to control hub 5532, e.g., in addition to, or instead of, being coupled directly to processor 5504.

In some embodiments, device 5500 comprises memory 5530 coupled to processor 5504 via memory interface 5534. Memory 5530 includes memory devices for storing information in device 5500.

In some embodiments, memory 5530 includes apparatus to maintain stable clocking as described with reference to various embodiments. Memory can include nonvolatile (state does not change if power to the memory device is interrupted) and/or volatile (state is indeterminate if power to the memory device is interrupted) memory devices. Memory device 5530 can be a dynamic random-access memory (DRAM) device, a static random-access memory (SRAM) device, flash memory device, phase-change memory device, or some other memory device having suitable performance to serve as process memory. In one embodiment, memory 5530 can operate as system memory for device 5500, to store data and instructions for use when the one or more processors 5504 executes an application or process. Memory 5530 can store application data, user data, music, photos, documents, or other data, as well as system data (whether long-term or temporary) related to the execution of the applications and functions of device 5500.

Elements of various embodiments and examples are also provided as a machine-readable medium (e.g., memory 5530) for storing the computer-executable instructions (e.g., instructions to implement any other processes discussed herein). The machine-readable medium (e.g., memory 5530) may include, but is not limited to, flash memory, optical disks, CD-ROMs, DVD ROMs, RAMs, EPROMs, EEPROMs, magnetic or optical cards, phase change memory (PCM), or other types of machine-readable media suitable for storing electronic or computer-executable instructions. For example, embodiments of the disclosure may be downloaded as a computer program (e.g., BIOS) which may be transferred from a remote computer (e.g., a server) to a requesting computer (e.g., a client) by way of data signals via a communication link (e.g., a modem or network connection).

In some embodiments, device 5500 comprises temperature measurement circuitries 5540, e.g., for measuring temperature of various components of device 5500. In an example, temperature measurement circuitries 5540 may be embedded, or coupled or attached to various components, whose temperature are to be measured and monitored. For example, temperature measurement circuitries 5540 may measure temperature of (or within) one or more of cores 5508 a, 5508 b, 5508c, voltage regulator 5514, memory 5530, a mother-board of SoC 5501, and/or any appropriate component of device 5500. In some embodiments, temperature measurement circuitries 5540 include a low power hybrid reverse (LPHR) bandgap reference (BGR) and digital temperature sensor (DTS), which utilizes subthreshold metal oxide semiconductor (MOS) transistor and the PNP parasitic Bi-polar Junction Transistor (BJT) device to form a reverse BGR that serves as the base for configurable BGR or DTS operating modes. The LPHR architecture uses low-cost MOS transistors and the standard parasitic PNP device. Based on a reverse bandgap voltage, the LPHR can work as a configurable BGR. By comparing the configurable BGR with the scaled base-emitter voltage, the circuit can also perform as a DTS with a linear transfer function with single-temperature trim for high accuracy.

In some embodiments, device 5500 comprises power measurement circuitries 5542, e.g., for measuring power consumed by one or more components of the device 5500. In an example, in addition to, or instead of, measuring power, the power measurement circuitries 5542 may measure voltage and/or current. In an example, the power measurement circuitries 5542 may be embedded, or coupled or attached to various components, whose power, voltage, and/or current consumption are to be measured and monitored. For example, power measurement circuitries 5542 may measure power, current and/or voltage supplied by one or more voltage regulators 5514, power supplied to SoC 5501, power supplied to device 5500, power consumed by processor 5504 (or any other component) of device 5500, etc.

In some embodiments, device 5500 comprises one or more voltage regulator circuitries, generally referred to as voltage regulator (VR) 5514. VR 5514 generates signals at appropriate voltage levels, which may be supplied to operate any appropriate components of the device 5500. Merely as an example, VR 5514 is illustrated to be supplying signals to processor 5504 of device 5500. In some embodiments, VR 5514 receives one or more Voltage Identification (VID) signals, and generates the voltage signal at an appropriate level, based on the VID signals. Various type of VRs may be utilized for the VR 5514. For example, VR 5514 may include a “buck” VR, “boost” VR, a combination of buck and boost VRs, low dropout (LDO) regulators, switching DC-DC regulators, constant-on-time controller-based DC-DC regulator, etc. Buck VR is generally used in power delivery applications in which an input voltage needs to be transformed to an output voltage in a ratio that is smaller than unity. Boost VR is generally used in power delivery applications in which an input voltage needs to be transformed to an output voltage in a ratio that is larger than unity. In some embodiments, each processor core has its own VR, which is controlled by PCU 5510 a/b and/or PMIC 5512. In some embodiments, each core has a network of distributed LDOs to provide efficient control for power management. The LDOs can be digital, analog, or a combination of digital or analog LDOs. In some embodiments, VR 5514 includes current tracking apparatus to measure current through power supply rail(s).

In some embodiments, VR 5514 includes a digital control scheme to manage states of a proportional-integral-derivative (PID) filter (also known as a digital Type-III compensator). The digital control scheme controls the integrator of the PID filter to implement non-linear control of saturating the duty cycle during which the proportional and derivative terms of the PID are set to 0 while the integrator and its internal states (previous values or memory) is set to a duty cycle that is the sum of the current nominal duty cycle plus a deltaD. The deltaD is the maximum duty cycle increment that is used to regulate a voltage regulator from ICCmin to ICCmax and is a configuration register that can be set post silicon. A state machine moves from a non-linear all ON state (which brings the output voltage Vout back to a regulation window) to an open loop duty cycle which maintains the output voltage slightly higher than the required reference voltage Vref. After a certain period in this state of open loop at the commanded duty cycle, the state machine then ramps down the open loop duty cycle value until the output voltage is close to the Vref commanded. As such, output chatter on the output supply from VR 5514 is completely eliminated (or substantially eliminated) and there is merely a single undershoot transition which could lead to a guaranteed Vmin based on a comparator delay and the di/dt of the load with the available output decoupling capacitance.

In some embodiments, VR 5514 includes a separate self-start controller, which is functional without fuse and/or trim information. The self-start controller protects VR 5514 against large inrush currents and voltage overshoots, while being capable of following a variable VID (voltage identification) reference ramp imposed by the system. In some embodiments, the self-start controller uses a relaxation oscillator built into the controller to set the switching frequency of the buck converter. The oscillator can be initialized using either a clock or current reference to be close to a desired operating frequency. The output of VR 5514 is coupled weakly to the oscillator to set the duty cycle for closed loop operation. The controller is naturally biased such that the output voltage is always slightly higher than the set point, eliminating the need for any process, voltage, and/or temperature (PVT) imposed trims.

In some embodiments, device 5500 comprises one or more clock generator circuitries, generally referred to as clock generator 5516. Clock generator 5516 generates clock signals at appropriate frequency levels, which may be supplied to any appropriate components of device 5500. Merely as an example, clock generator 5516 is illustrated to be supplying clock signals to processor 5504 of device 5500. In some embodiments, clock generator 5516 receives one or more Frequency Identification (FID) signals, and generates the clock signals at an appropriate frequency, based on the FID signals.

In some embodiments, device 5500 comprises battery 5518 supplying power to various components of device 5500. Merely as an example, battery 5518 is illustrated to be supplying power to processor 5504. Although not illustrated in the figures, device 5500 may comprise a charging circuitry, e.g., to recharge the battery, based on Alternating Current (AC) power supply received from an AC adaptor.

In some embodiments, battery 5518 periodically checks an actual battery capacity or energy with charge to a preset voltage (e.g., 4.1 V). The battery then decides of the battery capacity or energy. If the capacity or energy is insufficient, then an apparatus in or associated with the battery slightly increases charging voltage to a point where the capacity is sufficient (e.g. from 4.1 V to 4.11 V). The process of periodically checking and slightly increase charging voltage is performed until charging voltage reaches specification limit (e.g., 4.2 V). The scheme described herein has benefits such as battery longevity can be extended, risk of insufficient energy reserve can be reduced, burst power can be used as long as possible, and/or even higher burst power can be used.

In some embodiments, battery 5518 is a multi-battery system with workload dependent load-sharing mechanism. The mechanism is an energy management system that operates in three modes—energy saving mode, balancer mode, and turbo mode. The energy saving mode is a normal mode where the multiple batteries (collectively shown as battery 5518) provide power to their own set of loads with least resistive dissipation. In balancing mode, the batteries are connected through switches operating in active mode so that the current shared is inversely proportion to the corresponding battery state-of-charge. In turbo mode, both batteries are connected in parallel through switches (e.g., on-switches) to provide maximum power to a processor or load. In some embodiments, battery 5518 is a hybrid battery which comprising a fast charging battery and a high energy density battery. Fast charging battery (FC) means a battery capable of faster charging than high energy density battery (HE). FC may be today's Li-ion battery as it is capable of faster charging than HE. In some embodiments, a controller (part of battery 5518) optimizes the sequence and charging rate for the hybrid battery to maximize both the charging current and charging speed of the battery, while enabling longer battery life.

In some embodiments, the charging circuitry (e.g., 5518) comprises a buck-boost converter. This buck-boost converter comprises DrMOS or DrGaN devices used in place of half-bridges for traditional buck-boost converters. Various embodiments here are described with reference to DrMOS. However, the embodiments are applicable to DrGaN. The DrMOS devices allow for better efficiency in power conversion due to reduced parasitic and optimized MOSFET packaging. Since the dead-time management is internal to the DrMOS, the dead-time management is more accurate than for traditional buck-boost converters leading to higher efficiency in conversion. Higher frequency of operation allows for smaller inductor size, which in turn reduces the z-height of the charger comprising the DrMOS based buck-boost converter. The buck-boost converter of various embodiments comprises dual-folded bootstrap for DrMOS devices. In some embodiments, in addition to the traditional bootstrap capacitors, folded bootstrap capacitors are added that cross-couple inductor nodes to the two sets of DrMOS switches.

In some embodiments, device 5500 comprises Power Control Unit (PCU) 5510 (also referred to as Power Management Unit (PMU), Power Management Controller (PMC), Power Unit (p-unit), etc.). In an example, some sections of PCU 5510 may be implemented by one or more processing cores 5508, and these sections of PCU 5510 are symbolically illustrated using a dotted box and labelled PCU 5510 a. In an example, some other sections of PCU 5510 may be implemented outside the processing cores 5508, and these sections of PCU 5510 are symbolically illustrated using a dotted box and labelled as PCU 5510 b. PCU 5510 may implement various power management operations for device 5500. PCU 5510 may include hardware interfaces, hardware circuitries, connectors, registers, etc., as well as software components (e.g., drivers, protocol stacks), to implement various power management operations for device 5500.

In various embodiments, PCU or PMU 5510 is organized in a hierarchical manner forming a hierarchical power management (HPM). HPM of various embodiments builds a capability and infrastructure that allows for package level management for the platform, while still catering to islands of autonomy that might exist across the constituent die in the package. HPM does not assume a pre-determined mapping of physical partitions to domains. An HPM domain can be aligned with a function integrated inside a dielet, to a dielet boundary, to one or more dielets, to a companion die, or even a discrete CXL device. HPM addresses integration of multiple instances of the same die, mixed with proprietary functions or 3rd party functions integrated on the same die or separate die, and even accelerators connected via CXL (e.g., Flexbus) that may be inside the package, or in a discrete form factor.

HPM enables designers to meet the goals of scalability, modularity, and late binding. HPM also allows PMU functions that may already exist on other dice to be leveraged, instead of being disabled in the flat scheme. HPM enables management of any arbitrary collection of functions independent of their level of integration. HPM of various embodiments is scalable, modular, works with symmetric multi-chip processors (MCPs), and works with asymmetric MCPs. For example, HPM does not need a signal PM controller and package infrastructure to grow beyond reasonable scaling limits. HPM enables late addition of a die in a package without the need for change in the base die infrastructure. HPM addresses the need of disaggregated solutions having dies of different process technology nodes coupled in a single package. HPM also addresses the needs of companion die integration solutions—on and off package.

In various embodiments, each die (or dielet) includes a power management unit (PMU) or p-unit. For example, processor dies can have a supervisor p-unit, supervisee p-unit, or a dual role supervisor/supervisee p-unit. In some embodiments, an I/O die has its own dual role p-unit such as supervisor and/or supervisee p-unit. The p-units in each die can be instances of a generic p-unit. In one such example, all p-units have the same capability and circuits, but are configured (dynamically or statically) to take a role of a supervisor, supervisee, and/or both. In some embodiments, the p-units for compute dies are instances of a compute p-unit while p-units for IO dies are instances of an IO p-unit different from the compute p-unit. Depending on the role, p-unit acquires specific responsibilities to manage power of the multichip module and/or computing platform. While various p-units are described for dies in a multichip module or system-on-chip, a p-unit can also be part of an external device such as I/O device.

Here, the various p-units do not have to be the same. The HPM architecture can operate very different types of p-units. One common feature for the p-units is that they are expected to receive HPM messages and are expected to be able to comprehend them. In some embodiments, the p-unit of IO dies may be different than the p-unit of the compute dies. For example, the number of register instances of each class of register in the IO p-unit is different than those in the p-units of the compute dies. An IO die has the capability of being an HPM supervisor for CXL connected devices, but compute die may not need to have that capability. The IO and computes dice also have different firmware flows and possibly different firmware images. These are choices that an implementation can make. An HPM architecture can choose to have one superset firmware image and selectively execute flows that are relevant to the die type the firmware is associated with. Alternatively, there can be a customer firmware for each p-unit type; it can allow for more streamlined sizing of the firmware storage requirements for each p-unit type.

The p-unit in each die can be configured as a supervisor p-unit, supervisee p-unit or with a dual role of supervisor/supervisee. As such, p-units can perform roles of supervisor or supervisee for various domains. In various embodiments, each instance of p-unit is capable of autonomously managing local dedicated resources and contains structures to aggregate data and communicate between instances to enable shared resource management by the instance configured as the shared resource supervisor. A message and wire-based infrastructure is provided that can be duplicated and configured to facilitate management and flows between multiple p-units.

In some embodiments, power and thermal thresholds are communicated by a supervisor p-unit to supervisee p-units. For example, a supervisor p-unit learns of the workload (present and future) of each die, power measurements of each die, and other parameters (e.g., platform level power boundaries) and determines new power limits for each die. These power limits are then communicated by supervisor p-units to the supervisee p-units via one or more interconnects and fabrics. In some embodiments, a fabric indicates a group of fabrics and interconnect including a first fabric, a second fabric, and a fast response interconnect. In some embodiments, the first fabric is used for common communication between a supervisor p-unit and a supervisee p-unit. These common communications include change in voltage, frequency, and/or power state of a die which is planned based on a number of factors (e.g., future workload, user behavior, etc.). In some embodiments, the second fabric is used for higher priority communication between supervisor p-unit and supervisee p-unit. Example of higher priority communication include a message to throttle because of a possible thermal runaway condition, reliability issue, etc. In some embodiments, a fast response interconnect is used for communicating fast or hard throttle of all dies. In this case, a supervisor p-unit may send a fast throttle message to all other p-units, for example. In some embodiments, a fast response interconnect is a legacy interconnect whose function can be performed by the second fabric.

The HPM architecture of various embodiments enables scalability, modularity, and late binding of symmetric and/or asymmetric dies. Here, symmetric dies are dies of same size, type, and/or function, while asymmetric dies are dies of different size, type, and/or function. Hierarchical approach also allows PMU functions that may already exist on other dice to be leveraged, instead of being disabled in the traditional flat power management scheme. HPM does not assume a pre-determined mapping of physical partitions to domains. An HPM domain can be aligned with a function integrated inside a dielet, to a dielet boundary, to one or more dielets, to a companion die, or even a discrete CXL device. HPM enables management of any arbitrary collection of functions independent of their level of integration. In some embodiments, a p-unit is declared a supervisor p-unit based on one or more factors. These factors include memory size, physical constraints (e.g., number of pin-outs), and locations of sensors (e.g., temperature, power consumption, etc.) to determine physical limits of the processor.

The HPM architecture of various embodiments, provides a means to scale power management so that a single p-unit instance does not need to be aware of the entire processor. This enables power management at a smaller granularity and improves response times and effectiveness. Hierarchical structure maintains a monolithic view to the user. For example, at an operating system (OS) level, HPM architecture gives the OS a single PMU view even though the PMU is physically distributed in one or more supervisor-supervisee configurations.

In some embodiments, the HPM architecture is centralized where one supervisor controls all supervisees. In some embodiments, the HPM architecture is decentralized, wherein various p-units in various dies control overall power management by peer-to-peer communication. In some embodiments, the HPM architecture is distributed where there are different supervisors for different domains. One example of a distributed architecture is a tree-like architecture.

In some embodiments, device 5500 comprises Power Management Integrated Circuit (PMIC) 5512, e.g., to implement various power management operations for device 5500. In some embodiments, PMIC 5512 is a Reconfigurable Power Management ICs (RPMICs) and/or an IMVP (Intel® Mobile Voltage Positioning). In an example, the PMIC is within an IC die separate from processor 5504. The may implement various power management operations for device 5500. PMIC 5512 may include hardware interfaces, hardware circuitries, connectors, registers, etc., as well as software components (e.g., drivers, protocol stacks), to implement various power management operations for device 5500.

In an example, device 5500 comprises one or both PCU 5510 or PMIC 5512. In an example, any one of PCU 5510 or PMIC 5512 may be absent in device 5500, and hence, these components are illustrated using dotted lines.

Various power management operations of device 5500 may be performed by PCU 5510, by PMIC 5512, or by a combination of PCU 5510 and PMIC 5512. For example, PCU 5510 and/or PMIC 5512 may select a power state (e.g., P-state) for various components of device 5500. For example, PCU 5510 and/or PMIC 5512 may select a power state (e.g., in accordance with the ACPI (Advanced Configuration and Power Interface) specification) for various components of device 5500. Merely as an example, PCU 5510 and/or PMIC 5512 may cause various components of the device 5500 to transition to a sleep state, to an active state, to an appropriate C state (e.g., C0 state, or another appropriate C state, in accordance with the ACPI specification), etc. In an example, PCU 5510 and/or PMIC 5512 may control a voltage output by VR 5514 and/or a frequency of a clock signal output by the clock generator, e.g., by outputting the VID signal and/or the FID signal, respectively. In an example, PCU 5510 and/or PMIC 5512 may control battery power usage, charging of battery 5518, and features related to power saving operation.

The clock generator 5516 can comprise a phase locked loop (PLL), frequency locked loop (FLL), or any suitable clock source. In some embodiments, each core of processor 5504 has its own clock source. As such, each core can operate at a frequency independent of the frequency of operation of the other core. In some embodiments, PCU 5510 and/or PMIC 5512 performs adaptive or dynamic frequency scaling or adjustment. For example, clock frequency of a processor core can be increased if the core is not operating at its maximum power consumption threshold or limit. In some embodiments, PCU 5510 and/or PMIC 5512 determines the operating condition of each core of a processor, and opportunistically adjusts frequency and/or power supply voltage of that core without the core clocking source (e.g., PLL of that core) losing lock when the PCU 5510 and/or PMIC 5512 determines that the core is operating below a target performance level. For example, if a core is drawing current from a power supply rail less than a total current allocated for that core or processor 5504, then PCU 5510 and/or PMIC 5512 can temporality increase the power draw for that core or processor 5504 (e.g., by increasing clock frequency and/or power supply voltage level) so that the core or processor 5504 can perform at higher performance level. As such, voltage and/or frequency can be increased temporality for processor 5504 without violating product reliability.

In an example, PCU 5510 and/or PMIC 5512 may perform power management operations, e.g., based at least in part on receiving measurements from power measurement circuitries 5542, temperature measurement circuitries 5540, charge level of battery 5518, and/or any other appropriate information that may be used for power management. To that end, PMIC 5512 is communicatively coupled to one or more sensors to sense/detect various values/variations in one or more factors having an effect on power/thermal behavior of the system/platform. Examples of the one or more factors include electrical current, voltage droop, temperature, operating frequency, operating voltage, power consumption, inter-core communication activity, etc. One or more of these sensors may be provided in physical proximity (and/or thermal contact/coupling) with one or more components or logic/IP blocks of a computing system. Additionally, sensor(s) may be directly coupled to PCU 5510 and/or PMIC 5512 in at least one embodiment to allow PCU 5510 and/or PMIC 5512 to manage processor core energy at least in part based on value(s) detected by one or more of the sensors.

Also illustrated is an example software stack of device 5500 (although not all elements of the software stack are illustrated). Merely as an example, processors 5504 may execute application programs 5550, Operating System 5552, one or more Power Management (PM) specific application programs (e.g., generically referred to as PM applications 5558), and/or the like. PM applications 5558 may also be executed by the PCU 5510 and/or PMIC 5512. OS 5552 may also include one or more PM applications 5556a, 5556b, 5556c. The OS 5552 may also include various drivers 5554 a, 5554 b, 5554c, etc., some of which may be specific for power management purposes. In some embodiments, device 5500 may further comprise a Basic Input/output System (BIOS) 5520. BIOS 5520 may communicate with OS 5552 (e.g., via one or more drivers 5554), communicate with processors 5504, etc.

For example, one or more of PM applications 5558, 5556, drivers 5554, BIOS 5520, etc. may be used to implement power management specific tasks, e.g., to control voltage and/or frequency of various components of device 5500, to control wake-up state, sleep state, and/or any other appropriate power state of various components of device 5500, control battery power usage, charging of the battery 5518, features related to power saving operation, etc.

In some embodiments, battery 5518 is a Li-metal battery with a pressure chamber to allow uniform pressure on a battery. The pressure chamber is supported by metal plates (such as pressure equalization plate) used to give uniform pressure to the battery. The pressure chamber may include pressured gas, elastic material, spring plate, etc. The outer skin of the pressure chamber is free to bow, restrained at its edges by (metal) skin, but still exerts a uniform pressure on the plate that is compressing the battery cell. The pressure chamber gives uniform pressure to battery, which is used to enable high-energy density battery with, for example, 20% more battery life.

In some embodiments, battery 5518 includes hybrid technologies. For example, a mix of high energy density charge (e.g., Li-ion batteries) carrying device(s) and low energy density charge carrying devices (e.g., supercapacitor) are used as batteries or storage devices. In some embodiments, a controller (e.g., hardware, software, or a combination of them) is used analyze peak power patterns and minimizes the impact to overall lifespan of high energy density charge carrying device-based battery cells while maximizing service time for peak power shaving feature. The controller may be part of battery 5518 or part of p-unit 5510 b.

In some embodiments, pCode executing on PCU 5510 a/b has a capability to enable extra compute and telemetries resources for the runtime support of the pCode. Here pCode refers to a firmware executed by PCU 5510 a/b to manage performance of the SoC 5501. For example, pCode may set frequencies and appropriate voltages for the processor. Part of the pCode are accessible via OS 5552. In various embodiments, mechanisms and methods are provided that dynamically change an Energy Performance Preference (EPP) value based on workloads, user behavior, and/or system conditions. There may be a well-defined interface between OS 5552 and the pCode. The interface may allow or facilitate the software configuration of several parameters and/or may provide hints to the pCode. As an example, an EPP parameter may inform a pCode algorithm as to whether performance or battery life is more important.

This support may be done as well by the OS 5552 by including machine-learning support as part of OS 5552 and either tuning the EPP value that the OS hints to the hardware (e.g., various components of SoC 5501) by machine-learning prediction, or by delivering the machine-learning prediction to the pCode in a manner similar to that done by a Dynamic Tuning Technology (DTT) driver. In this model, OS 5552 may have visibility to the same set of telemetries as are available to a DTT. As a result of a DTT machine-learning hint setting, pCode may tune its internal algorithms to achieve optimal power and performance results following the machine-learning prediction of activation type. The pCode as example may increase the responsibility for the processor utilization change to enable fast response for user activity, or may increase the bias for energy saving either by reducing the responsibility for the processor utilization or by saving more power and increasing the performance lost by tuning the energy saving optimization. This approach may facilitate saving more battery life in case the types of activities enabled lose some performance level over what the system can enable. The pCode may include an algorithm for dynamic EPP that may take the two inputs, one from OS 5552 and the other from software such as DTT, and may selectively choose to provide higher performance and/or responsiveness. As part of this method, the pCode may enable in the DTT an option to tune its reaction for the DTT for different types of activity.

In some embodiments, pCode improves the performance of the SoC in battery mode. In some embodiments, pCode allows drastically higher SoC peak power limit levels (and thus higher Turbo performance) in battery mode. In some embodiments, pCode implements power throttling and is part of Intel's Dynamic Tuning Technology (DTT). In various embodiments, the peak power limit is referred to PL4. However, the embodiments are applicable to other peak power limits. In some embodiments, pCode sets the Vth threshold voltage (the voltage level at which the platform will throttle the SoC) in such a way as to prevent the system from unexpected shutdown (or black screening). In some embodiments, pCode calculates the Psoc,pk SoC Peak Power Limit (e.g., PL4), according to the threshold voltage (Vth). These are two dependent parameters, if one is set, the other can be calculated. pCode is used to optimally set one parameter (Vth) based on the system parameters, and the history of the operation. In some embodiments, pCode provides a scheme to dynamically calculate the throttling level (Psoc,th) based on the available battery power (which changes slowly) and set the SoC throttling peak power (Psoc,th). In some embodiments, pCode decides the frequencies and voltages based on Psoc,th. In this case, throttling events have less negative effect on the SoC performance Various embodiments provide a scheme which allows maximum performance (Pmax) framework to operate.

In some embodiments, VR 5514 includes a current sensor to sense and/or measure current through a high-side switch of VR 5514. In some embodiments the current sensor uses an amplifier with capacitively coupled inputs in feedback to sense the input offset of the amplifier, which can be compensated for during measurement. In some embodiments, the amplifier with capacitively coupled inputs in feedback is used to operate the amplifier in a region where the input common-mode specifications are relaxed, so that the feedback loop gain and/or bandwidth is higher. In some embodiments, the amplifier with capacitively coupled inputs in feedback is used to operate the sensor from the converter input voltage by employing high-PSRR (power supply rejection ratio) regulators to create a local, clean supply voltage, causing less disruption to the power grid in the switch area. In some embodiments, a variant of the design can be used to sample the difference between the input voltage and the controller supply, and recreate that between the drain voltages of the power and replica switches. This allows the sensor to not be exposed to the power supply voltage. In some embodiments, the amplifier with capacitively coupled inputs in feedback is used to compensate for power delivery network related (PDN-related) changes in the input voltage during current sensing.

Some embodiments use three components to adjust the peak power of SoC 5501 based on the states of a USB TYPE-C device 5529. These components include OS Peak Power Manager (part of OS 5552), USB TYPE-C Connector Manager (part of OS 5552), and USB TYPE-C Protocol Device Driver (e.g., one of drivers 5554 a, 5554 b, 5554 c). In some embodiments, the USB TYPE-C Connector Manager sends a synchronous request to the OS Peak Power Manager when a USB TYPE-C power sink device is attached or detached from SoC 5501, and the USB TYPE-C Protocol Device Driver sends a synchronous request to the Peak Power Manager when the power sink transitions device state. In some embodiments, the Peak Power Manager takes power budget from the CPU when the USB TYPE-C connector is attached to a power sink and is active (e.g., high power device state). In some embodiments, the Peak Power Manager gives back the power budget to the CPU for performance when the USB TYPE-C connector is either detached or the attached and power sink device is idle (lowest device state).

In some embodiments, logic is provided to dynamically pick the best operating processing core for BIOS power-up flows and sleep exit flows (e.g., S3, S4, and/or S5). The selection of the bootstrap processor (BSP) is moved to an early power-up time instead of a fixed hardware selection at any time. For maximum boot performance, the logic selects the fastest capable core as the BSP at an early power-up time. In addition, for maximum power saving, the logic selects the most power efficient core as the BSP. Processor or switching for selecting the BSP happens during the boot-up as well as power-up flows (e.g., S3, S4, and/or S5 flows).

In some embodiments, the memories herein are organized in multi-level memory architecture and their performance is governed by a decentralized scheme. The decentralized scheme includes p-unit 5510 and memory controllers. In some embodiments, the scheme dynamically balances a number of parameters such as power, thermals, cost, latency and performance for memory levels that are progressively further away from the processor in platform 5500 based on how applications are using memory levels that are further away from processor cores. In some examples, the decision making for the state of the far memory (FM) is decentralized. For example, a processor power management unit (p-unit), near memory controller (NMC), and/or far memory host controller (FMHC) makes decisions about the power and/or performance state of the FM at their respective levels. These decisions are coordinated to provide the most optimum power and/or performance state of the FM for a given time. The power and/or performance state of the memories adaptively change to changing workloads and other parameters even when the processor(s) is in a particular power state.

In some embodiments, a hardware and software coordinated processor power state policy (e.g., policy for C-state) is implemented that delivers optimal power state selection by taking in to account the performance and/or responsiveness needs of thread expected to be scheduled on the core entering idle, to achieve improved instructions per cycle (IPC) and performance for cores running user critical tasks. The scheme provides the ability to deliver responsiveness gains for important and/or user-critical threads running on a system-on-chip. P-unit 5510 which coupled to the plurality of processing cores, receives a hint from operating system 5552 indicative of a bias towards a power state or performance state for at least one of the processing cores of the plurality of processing cores based on a priority of a thread in context switch.

Reference in the specification to “an embodiment,” “one embodiment,” “some embodiments,” or “other embodiments” means that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least some embodiments, but not necessarily all embodiments. The various appearances of “an embodiment,” “one embodiment,” or “some embodiments” are not necessarily all referring to the same embodiments. If the specification states a component, feature, structure, or characteristic “may,” “might,” or “could” be included, that particular component, feature, structure, or characteristic is not required to be included. If the specification or claim refers to “a” or “an” element, that does not mean there is only one of the elements. If the specification or claims refer to “an additional” element, that does not preclude there being more than one of the additional elements.

Throughout the specification, and in the claims, the term “connected” means a direct connection, such as electrical, mechanical, or magnetic connection between the things that are connected, without any intermediary devices.

The term “coupled” means a direct or indirect connection, such as a direct electrical, mechanical, or magnetic connection between the things that are connected or an indirect connection, through one or more passive or active intermediary devices.

The term “adjacent” here generally refers to a position of a thing being next to (e.g., immediately next to or close to with one or more things between them) or adjoining another thing (e.g., abutting it).

The term “circuit” or “module” may refer to one or more passive and/or active components that are arranged to cooperate with one another to provide a desired function.

The term “signal” may refer to at least one current signal, voltage signal, magnetic signal, or data/clock signal. The meaning of “a,” “an,” and “the” include plural references. The meaning of “in” includes “in” and “on.”

The term “analog signal” is any continuous signal for which the time varying feature (variable) of the signal is a representation of some other time varying quantity, i.e., analogous to another time varying signal.

The term “digital signal” is a physical signal that is a representation of a sequence of discrete values (a quantified discrete-time signal), for example of an arbitrary bit stream, or of a digitized (sampled and analog-to-digital converted) analog signal.

The term “scaling” generally refers to converting a design (schematic and layout) from one process technology to another process technology and may be subsequently being reduced in layout area. In some cases, scaling also refers to upsizing a design from one process technology to another process technology and may be subsequently increasing layout area. The term “scaling” generally also refers to downsizing or upsizing layout and devices within the same technology node. The term “scaling” may also refer to adjusting (e.g., slowing down or speeding up—i.e. scaling down, or scaling up respectively) of a signal frequency relative to another parameter, for example, power supply level.

The terms “substantially,” “close,” “approximately,” “near,” and “about,” generally refer to being within +/−10% of a target value.

Unless otherwise specified the use of the ordinal adjectives “first,” “second,” and “third,” etc., to describe a common object, merely indicate that different instances of like objects are being referred to and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking or in any other manner

For the purposes of the present disclosure, phrases “A and/or B” and “A or B” mean (A), (B), or (A and B). For the purposes of the present disclosure, the phrase “A, B, and/or C” means (A), (B), (C), (A and B), (A and C), (B and C), or (A, B and C).

The terms “left,” “right,” “front,” “back,” “top,” “bottom,” “over,” “under,” and the like in the description and in the claims, if any, are used for descriptive purposes and not necessarily for describing permanent relative positions.

It is pointed out that those elements of the figures having the same reference numbers (or names) as the elements of any other figure can operate or function in any manner similar to that described but are not limited to such.

For purposes of the embodiments, the transistors in various circuits and logic blocks described here are metal oxide semiconductor (MOS) transistors or their derivatives, where the MOS transistors include drain, source, gate, and bulk terminals. The transistors and/or the MOS transistor derivatives also include Tri-Gate and FinFET transistors, Gate All Around Cylindrical Transistors, Tunneling FET (TFET), Square Wire, or Rectangular Ribbon Transistors, ferroelectric FET (FeFETs), or other devices implementing transistor functionality like carbon nanotubes or spintronic devices. MOSFET symmetrical source and drain terminals i.e., are identical terminals and are interchangeably used here. A TFET device, on the other hand, has asymmetric Source and Drain terminals. Those skilled in the art will appreciate that other transistors, for example, Bi-polar junction transistors (BJT PNP/NPN), BiCMOS, CMOS, etc., may be used without departing from the scope of the disclosure.

Here the term “die” generally refers to a single continuous piece of semiconductor material (e.g. silicon) where transistors or other components making up a processor core may reside. Multi-core processors may have two or more processors on a single die, but alternatively, the two or more processors may be provided on two or more respective dies. Each die has a dedicated power controller or power control unit (p-unit) power controller or power control unit (p-unit) which can be dynamically or statically configured as a supervisor or supervisee. In some examples, dies are of the same size and functionality i.e., symmetric cores. However, dies can also be asymmetric. For example, some dies have different size and/or function than other dies. Each processor may also be a dielet or chiplet. Here the term “dielet” or “chiplet” generally refers to a physically distinct semiconductor die, typically connected to an adjacent die in a way that allows the fabric across a die boundary to function like a single fabric rather than as two distinct fabrics. Thus at least some dies may be dielets. Each dielet may include one or more p-units which can be dynamically or statically configured as a supervisor, supervisee or both.

Here the term “fabric” generally refers to communication mechanism having a known set of sources, destinations, routing rules, topology and other properties. The sources and destinations may be any type of data handling functional unit such as power management units. Fabrics can be two-dimensional spanning along an x-y plane of a die and/or three-dimensional (3D) spanning along an x-y-z plane of a stack of vertical and horizontally positioned dies. A single fabric may span multiple dies. A fabric can take any topology such as mesh topology, star topology, daisy chain topology. A fabric may be part of a network-on-chip (NoC) with multiple agents. These agents can be any functional unit.

Here, the term “processor core” generally refers to an independent execution unit that can run one program thread at a time in parallel with other cores. A processor core may include a dedicated power controller or power control unit (p-unit) which can be dynamically or statically configured as a supervisor or supervisee. This dedicated p-unit is also referred to as an autonomous p-unit, in some examples. In some examples, all processor cores are of the same size and functionality i.e., symmetric cores. However, processor cores can also be asymmetric. For example, some processor cores have different size and/or function than other processor cores. A processor core can be a virtual processor core or a physical processor core.

Here, the term “interconnect” refers to a communication link, or channel, between two or more points or nodes. It may comprise one or more separate conduction paths such as wires, vias, waveguides, passive components, and/or active components. It may also comprise a fabric.

Here the term “interface” generally refers to software and/or hardware used to communicate with an interconnect. An interface may include logic and I/O driver/receiver to send and receive data over the interconnect or one or more wires.

Here the term “domain” generally refers to a logical or physical perimeter that has similar properties (e.g., supply voltage, operating frequency, type of circuits or logic, and/or workload type) and/or is controlled by a particular agent. For example, a domain may be a group of logic units or function units that are controlled by a particular supervisor. A domain may also be referred to as an Autonomous Perimeter (AP). A domain can be an entire system-on-chip (SoC) or part of the SoC, and is governed by a p-unit.

Here the term “supervisor” generally refers to a power controller, or power management, unit (a “p-unit”), which monitors and manages power and performance related parameters for one or more associated power domains, either alone or in cooperation with one or more other p-units. Power/performance related parameters may include but are not limited to domain power, platform power, voltage, voltage domain current, die current, load-line, temperature, device latency, utilization, clock frequency, processing efficiency, current/future workload information, and other parameters. It may determine new power or performance parameters (limits, average operational, etc.) for the one or more domains. These parameters may then be communicated to supervisee p-units, or directly to controlled or monitored entities such as VR or clock throttle control registers, via one or more fabrics and/or interconnects. A supervisor learns of the workload (present and future) of one or more dies, power measurements of the one or more dies, and other parameters (e.g., platform level power boundaries) and determines new power limits for the one or more dies. These power limits are then communicated by supervisor p-units to the supervisee p-units via one or more fabrics and/or interconnect. In examples where a die has one p-unit, a supervisor (Svor) p-unit is also referred to as supervisor die.

Here the term “supervisee” generally refers to a power controller, or power management, unit (a “p-unit”), which monitors and manages power and performance related parameters for one or more associated power domains, either alone or in cooperation with one or more other p-units and receives instructions from a supervisor to set power and/or performance parameters (e.g., supply voltage, operating frequency, maximum current, throttling threshold, etc.) for its associated power domain. In examples where a die has one p-unit, a supervisee (Svee) p-unit may also be referred to as a supervisee die. Note that a p-unit may serve either as a Svor, a Svee, or both a Svor/Svee p-unit.

Furthermore, the particular features, structures, functions, or characteristics may be combined in any suitable manner in one or more embodiments. For example, a first embodiment may be combined with a second embodiment anywhere the particular features, structures, functions, or characteristics associated with the two embodiments are not mutually exclusive.

While the disclosure has been described in conjunction with specific embodiments thereof, many alternatives, modifications and variations of such embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. The embodiments of the disclosure are intended to embrace all such alternatives, modifications, and variations as to fall within the broad scope of the appended claims.

In addition, well-known power/ground connections to integrated circuit (IC) chips and other components may or may not be shown within the presented figures, for simplicity of illustration and discussion, and so as not to obscure the disclosure. Further, arrangements may be shown in block diagram form in order to avoid obscuring the disclosure, and also in view of the fact that specifics with respect to implementation of such block diagram arrangements are highly dependent upon the platform within which the present disclosure is to be implemented (i.e., such specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the disclosure, it should be apparent to one skilled in the art that the disclosure can be practiced without, or with variation of, these specific details. The description is thus to be regarded as illustrative instead of limiting.

Various embodiments are described as examples. The examples can be combined in any suitable manner For instance, example 5 can be combined with example 3 and/or example 7.

EXAMPLE 1

An apparatus comprising: a voltage regulator to provide power to an output supply rail; and a current sensor coupled to the voltage regulator, wherein the current sensor includes a Kalman filter with a first logic to estimate equivalent resistance through the output supply rail, and with a second logic to track a transient behavior on the output supply rail.

EXAMPLE 2

The apparatus of example 1, wherein a portion of the Kalman filter is bypassed based on the second logic tracking the transient behavior.

EXAMPLE 3

The apparatus of example 1, wherein the Kalman filter includes a state prediction logic coupled to the first logic.

EXAMPLE 4

The apparatus of example 3, wherein the current sensor comprises a multiplexer to selectively provide an estimated model for a difference in inductor current samples to the state prediction logic based on the second logic tracking the transient behavior.

EXAMPLE 5

The apparatus of example 1, wherein the current sensor comprises an analog-to-digital converter (ADC) coupled to the voltage regulator, wherein the ADC is to provide digital representations of one or more parameters of the voltage regulator to the first logic and the second logic.

EXAMPLE 6

The apparatus of example 1 comprises a health monitor to monitor health of the voltage regulator based on the estimated equivalent resistance from the current sensor, wherein the health monitor is to shut down the voltage regulator if aging or thermal properties are above a safe threshold.

EXAMPLE 7

The apparatus of example 1 comprises an efficiency monitor to monitor efficiency of the voltage regulator based on the estimated equivalent resistance from the current sensor.

EXAMPLE 8

The apparatus of claim 1, wherein the voltage regulator comprises a DC-DC converter.

EXAMPLE 9

The apparatus of example 1, wherein the current sensor is a digital current sensor.

EXAMPLE 10

The apparatus of example 5, wherein the one or more parameters include: voltage on a switching node coupled to a high-side switch and a low-side switch; input supply voltage to the voltage regulator; or output supply voltage of the voltage regulator.

EXAMPLE 11

An apparatus comprising: a DC-DC converter to provide power to an output supply rail; and a current sensor coupled to the DC-DC converter, the current sensor comprising a first Kalman filter and a second Kalman filter parallel to the first Kalman filter, wherein the second Kalman filter is to generate an estimated equivalent resistance through the output supply rail and to provide that estimated equivalent resistance to the first Kalman filter.

EXAMPLE 12

The apparatus of example 11, wherein the current sensor includes circuitry to track a transient behavior on the output supply rail.

EXAMPLE 13

The apparatus of example 12, wherein a portion of the first Kalman filter is bypassed based on the circuitry tracking the transient behavior.

EXAMPLE 14

The apparatus of example 12, wherein the current sensor comprises a multiplexer to selectively provide an estimated model for a difference in inductor current samples to a state prediction logic based on the circuitry tracking the transient behavior.

EXAMPLE 15

A system comprising: a processor; a memory coupled to the processor; and a wireless interface communicatively coupled to the processor, wherein the processor includes: a DC-DC converter to provide power to an output supply rail; and a current sensor coupled to the DC-DC converter, the current sensor comprising a first Kalman filter and a second Kalman filter parallel to the first Kalman filter, wherein the second Kalman filter is to generate an estimated equivalent resistance through the output supply rail and to provide that estimated equivalent resistance to the first Kalman filter.

EXAMPLE 16

The system of example 15, wherein the current sensor includes circuitry to track a transient behavior on the output supply rail.

EXAMPLE 17

The system of example 16, wherein a portion of the first Kalman filter is bypassed based on the circuitry tracking the transient behavior.

EXAMPLE 18

The system of example 16, wherein the current sensor comprises a multiplexer to selectively provide an estimated model for a difference in inductor current samples to a state prediction logic based on the circuitry tracking the transient behavior.

EXAMPLE 19

The system of example 16, wherein the current sensor comprises an analog-to-digital converter (ADC) coupled to the DC-DC converter, wherein the ADC is to provide digital representations of one or more parameters of the DC-DC converter to the first Kalman filter, the second Kalman filter, and the circuitry.

EXAMPLE 20

The system of example 19, wherein the one or more parameters include: voltage on a switching node coupled to a high-side switch and a low-side switch; input supply voltage to the voltage regulator; and/or output supply voltage of the voltage regulator.

An abstract is provided that will allow the reader to ascertain the nature and gist of the technical disclosure. The abstract is submitted with the understanding that it will not be used to limit the scope or meaning of the claims. The following claims are hereby incorporated into the detailed description, with each claim standing on its own as a separate embodiment. 

What is claimed is:
 1. An apparatus comprising: a voltage regulator to provide power to an output supply rail; and a current sensor coupled to the voltage regulator, wherein the current sensor includes a Kalman filter with a first logic to estimate equivalent resistance through the output supply rail, and with a second logic to track a transient behavior on the output supply rail.
 2. The apparatus of claim 1, wherein a portion of the Kalman filter is bypassed based on the second logic tracking the transient behavior.
 3. The apparatus of claim 1, wherein the Kalman filter includes a state prediction logic coupled to the first logic.
 4. The apparatus of claim 3, wherein the current sensor comprises a multiplexer to selectively provide an estimated model for a difference in inductor current samples to the state prediction logic based on the second logic tracking the transient behavior.
 5. The apparatus of claim 1, wherein the current sensor comprises an analog-to-digital converter (ADC) coupled to the voltage regulator, wherein the ADC is to provide digital representations of one or more parameters of the voltage regulator to the first logic and the second logic.
 6. The apparatus of claim 1 comprises a health monitor to monitor health of the voltage regulator based on the estimated equivalent resistance from the current sensor, wherein the health monitor is to shut down the voltage regulator if aging or thermal properties are above a safe threshold.
 7. The apparatus of claim 1 comprises an efficiency monitor to monitor efficiency of the voltage regulator based on the estimated equivalent resistance from the current sensor.
 8. The apparatus of claim 1, wherein the voltage regulator comprises a DC-DC converter.
 9. The apparatus of claim 1, wherein the current sensor is a digital current sensor.
 10. The apparatus of claim 5, wherein the one or more parameters include: voltage on a switching node coupled to a high-side switch and a low-side switch; input supply voltage to the voltage regulator; or output supply voltage of the voltage regulator.
 11. An apparatus comprising: a DC-DC converter to provide power to an output supply rail; and a current sensor coupled to the DC-DC converter, the current sensor comprising a first Kalman filter and a second Kalman filter parallel to the first Kalman filter, wherein the second Kalman filter is to generate an estimated equivalent resistance through the output supply rail and to provide that estimated equivalent resistance to the first Kalman filter.
 12. The apparatus of claim 11, wherein the current sensor includes circuitry to track a transient behavior on the output supply rail.
 13. The apparatus of claim 12, wherein a portion of the first Kalman filter is bypassed based on the circuitry tracking the transient behavior.
 14. The apparatus of claim 12, wherein the current sensor comprises a multiplexer to selectively provide an estimated model for a difference in inductor current samples to a state prediction logic based on the circuitry tracking the transient behavior.
 15. A system comprising: a processor; a memory coupled to the processor; and a wireless interface communicatively coupled to the processor, wherein the processor includes: a DC-DC converter to provide power to an output supply rail; and a current sensor coupled to the DC-DC converter, the current sensor comprising a first Kalman filter and a second Kalman filter parallel to the first Kalman filter, wherein the second Kalman filter is to generate an estimated equivalent resistance through the output supply rail and to provide that estimated equivalent resistance to the first Kalman filter.
 16. The system of claim 15, wherein the current sensor includes circuitry to track a transient behavior on the output supply rail.
 17. The system of claim 16, wherein a portion of the first Kalman filter is bypassed based on the circuitry tracking the transient behavior.
 18. The system of claim 16, wherein the current sensor comprises a multiplexer to selectively provide an estimated model for a difference in inductor current samples to a state prediction logic based on the circuitry tracking the transient behavior.
 19. The system of claim 16, wherein the current sensor comprises an analog-to-digital converter (ADC) coupled to the DC-DC converter, wherein the ADC is to provide digital representations of one or more parameters of the DC-DC converter to the first Kalman filter, the second Kalman filter, and the circuitry.
 20. The system of claim 19, wherein the one or more parameters include: voltage on a switching node coupled to a high-side switch and a low-side switch; input supply voltage to the voltage regulator; or output supply voltage of the voltage regulator. 